On the feasibility of internet-scale author identification A Narayanan, H Paskov, NZ Gong, J Bethencourt, E Stefanov, ECR Shin, ... 2012 IEEE Symposium on Security and Privacy, 300-314, 2012 | 401 | 2012 |
Exploiting social network structure for person-to-person sentiment analysis R West, HS Paskov, J Leskovec, C Potts Transactions of the Association for Computational Linguistics 2, 297-310, 2014 | 284 | 2014 |
The failure of noise-based non-continuous audio captchas E Bursztein, R Beauxis, H Paskov, D Perito, C Fabry, J Mitchell 2011 IEEE symposium on security and privacy, 19-31, 2011 | 124 | 2011 |
Multitask learning improves prediction of cancer drug sensitivity H Yuan, I Paskov, H Paskov, AJ González, CS Leslie Scientific reports 6 (1), 31619, 2016 | 120 | 2016 |
A promising direction for web tracking countermeasures J Bau, J Mayer, H Paskov, JC Mitchell Proceedings of W2SP, 2013 | 61 | 2013 |
Compressive feature learning HS Paskov, R West, JC Mitchell, T Hastie Advances in Neural Information Processing Systems 26, 2013 | 21 | 2013 |
Crosslingual document embedding as reduced-rank ridge regression M Josifoski, IS Paskov, HS Paskov, M Jaggi, R West Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019 | 15 | 2019 |
A regularization framework for active learning from imbalanced data HS Paskov Massachusetts Institute of Technology, 2010 | 4 | 2010 |
Learning high order feature interactions with fine control kernels H Paskov, A Paskov, R West arXiv preprint arXiv:2002.03298, 2020 | 3 | 2020 |
Data representation and compression using linear-programming approximations HS Paskov, JC Mitchell, TJ Hastie arXiv preprint arXiv:1511.06606, 2015 | 2 | 2015 |
Fast Algorithms for Learning with Long N-grams via Suffix Tree Based Matrix Multiplication. HS Paskov, JC Mitchell, TJ Hastie UAI, 672-681, 2015 | 1 | 2015 |
An efficient algorithm for large scale compressive feature learning H Paskov, J Mitchell, T Hastie Artificial Intelligence and Statistics, 760-768, 2014 | 1 | 2014 |
A Practitioners Guide to Differentially Private Convex Optimization R McKenna, H Paskov, K Talwar | | 2021 |
Learning with N-Grams: From Massive Scales to Compressed Representations HS Paskov Stanford University, 2017 | | 2017 |
Exploiting Social Network Structure for Person-to-Person Sentiment Analysis (Supplementary Material to [WPLP14]) R West, HS Paskov, J Leskovec, C Potts | | |
Supplementary Material for Compressive Feature Learning HS Paskov, R West, JC Mitchell, TJ Hastie | | |
Supplementary Material for An Efficient Algorithm for Large Scale Compressive Feature Learning H Paskov | | |